Q
and R
.
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#include <ekf_templ.h>
Public Member Functions | |
EKFful_unQR (RV rx, RV ry, RV ru, RV rQR) | |
Default constructor. | |
void | condition (const vec &QR0) |
Substitute val for rvc . | |
void | set_parameters (diffbifn *pfxu, diffbifn *phxu, const mat Q0, const mat R0) |
Set nonlinear functions for mean values and covariance matrices. | |
void | bayes (const vec &dt) |
Here dt = [yt;ut] of appropriate dimensions. | |
void | set_est (vec mu0, mat P0) |
set estimates | |
const epdf & | _epdf () const |
dummy! | |
virtual void | bayesB (const mat &Dt) |
Batch Bayes rule (columns of Dt are observations). | |
virtual double | logpred (const vec &dt) const |
const RV & | _rv () const |
access function | |
double | _ll () const |
access function | |
void | set_evalll (bool evl0) |
access function | |
virtual BM * | _copy_ (bool changerv=false) |
const RV & | _rvc () const |
access function | |
Public Attributes | |
vec | mu |
Mean value of the posterior density. | |
mat | P |
Variance of the posterior density. | |
bool | evalll |
double | ll |
Protected Attributes | |
int | dimx |
int | dimy |
int | dimu |
mat | A |
mat | B |
mat | C |
mat | D |
mat | R |
mat | Q |
mat | _Pp |
mat | _Ry |
mat | _iRy |
mat | _K |
bool | evalll |
If true, the filter will compute likelihood of the data record and store it in ll . Set to false if you want to save computational time. | |
double | ll |
Logarithm of marginalized data likelihood. | |
RV | rv |
Random variable of the posterior. | |
RV | rvc |
Identificator of the conditioning variable. | |
Friends | |
std::ostream & | operator<< (std::ostream &os, const KalmanFull &kf) |
print elements of KF |
Q
and R
. virtual double BM::logpred | ( | const vec & | dt | ) | const [inline, virtual, inherited] |
virtual BM* BM::_copy_ | ( | bool | changerv = false |
) | [inline, virtual, inherited] |
Copy function required in vectors, Arrays of BM etc. Have to be DELETED manually! Prototype: BM* _copy_(){BM Tmp*=new Tmp(this*); return Tmp; }
Reimplemented in ARX.
Referenced by MixEF::MixEF().